Ce-daros
commented
3 months ago And Qwen1.5-0.5B works very well:
(llm-cpp) D:\Users\Documents\Projects\llama-cpp>server.exe -m "qwen1_5-0_5b-chat-q6_k.gguf" -ngl 999
{"tid":"4428","timestamp":1719324251,"level":"INFO","function":"main","line":2943,"msg":"build info","build":1,"commit":"adbd0dc"}
{"tid":"4428","timestamp":1719324251,"level":"INFO","function":"main","line":2950,"msg":"system info","n_threads":11,"n_threads_batch":-1,"total_threads":22,"system_info":"AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 1 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | "}
llama_model_loader: loaded meta data with 21 key-value pairs and 291 tensors from qwen1_5-0_5b-chat-q6_k.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = qwen2
llama_model_loader: - kv 1: general.name str = Qwen1.5-0.5B-Chat-AWQ-fp16
llama_model_loader: - kv 2: qwen2.block_count u32 = 24
llama_model_loader: - kv 3: qwen2.context_length u32 = 32768
llama_model_loader: - kv 4: qwen2.embedding_length u32 = 1024
llama_model_loader: - kv 5: qwen2.feed_forward_length u32 = 2816
llama_model_loader: - kv 6: qwen2.attention.head_count u32 = 16
llama_model_loader: - kv 7: qwen2.attention.head_count_kv u32 = 16
llama_model_loader: - kv 8: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 9: qwen2.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 10: qwen2.use_parallel_residual bool = true
llama_model_loader: - kv 11: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 12: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 13: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 14: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 15: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 16: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 17: tokenizer.ggml.bos_token_id u32 = 151643
llama_model_loader: - kv 18: tokenizer.chat_template str = {% for message in messages %}{{'<|im_...
llama_model_loader: - kv 19: general.quantization_version u32 = 2
llama_model_loader: - kv 20: general.file_type u32 = 18
llama_model_loader: - type f32: 121 tensors
llama_model_loader: - type q6_K: 170 tensors
llm_load_vocab: missing pre-tokenizer type, using: 'default'
llm_load_vocab:
llm_load_vocab: ************************************
llm_load_vocab: GENERATION QUALITY WILL BE DEGRADED!
llm_load_vocab: CONSIDER REGENERATING THE MODEL
llm_load_vocab: ************************************
llm_load_vocab:
llm_load_vocab: special tokens definition check successful ( 293/151936 ).
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = qwen2
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 151936
llm_load_print_meta: n_merges = 151387
llm_load_print_meta: n_ctx_train = 32768
llm_load_print_meta: n_embd = 1024
llm_load_print_meta: n_head = 16
llm_load_print_meta: n_head_kv = 16
llm_load_print_meta: n_layer = 24
llm_load_print_meta: n_rot = 64
llm_load_print_meta: n_embd_head_k = 64
llm_load_print_meta: n_embd_head_v = 64
llm_load_print_meta: n_gqa = 1
llm_load_print_meta: n_embd_k_gqa = 1024
llm_load_print_meta: n_embd_v_gqa = 1024
llm_load_print_meta: f_norm_eps = 0.0e+00
llm_load_print_meta: f_norm_rms_eps = 1.0e-06
llm_load_print_meta: f_clamp_kqv = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: f_logit_scale = 0.0e+00
llm_load_print_meta: n_ff = 2816
llm_load_print_meta: n_expert = 0
llm_load_print_meta: n_expert_used = 0
llm_load_print_meta: causal attn = 1
llm_load_print_meta: pooling type = 0
llm_load_print_meta: rope type = 2
llm_load_print_meta: rope scaling = linear
llm_load_print_meta: freq_base_train = 1000000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_yarn_orig_ctx = 32768
llm_load_print_meta: rope_finetuned = unknown
llm_load_print_meta: ssm_d_conv = 0
llm_load_print_meta: ssm_d_inner = 0
llm_load_print_meta: ssm_d_state = 0
llm_load_print_meta: ssm_dt_rank = 0
llm_load_print_meta: model type = 0.5B
llm_load_print_meta: model ftype = Q6_K
llm_load_print_meta: model params = 619.57 M
llm_load_print_meta: model size = 485.07 MiB (6.57 BPW)
llm_load_print_meta: general.name = Qwen1.5-0.5B-Chat-AWQ-fp16
llm_load_print_meta: BOS token = 151643 '<|endoftext|>'
llm_load_print_meta: EOS token = 151645 '<|im_end|>'
llm_load_print_meta: PAD token = 151643 '<|endoftext|>'
llm_load_print_meta: LF token = 148848 'ÄĬ'
llm_load_print_meta: EOT token = 151645 '<|im_end|>'
[SYCL] call ggml_init_sycl
ggml_init_sycl: GGML_SYCL_DEBUG: 0
ggml_init_sycl: GGML_SYCL_F16: no
found 1 SYCL devices:
| | | | |Max | |Max |Global |
|
| | | | |compute|Max work|sub |mem |
|
|ID| Device Type| Name|Version|units |group |group|size | Driver version|
|--|-------------------|---------------------------------------|-------|-------|--------|-----|-------|---------------------|
| 0| [level_zero:gpu:0]| Intel Arc Graphics| 1.3| 128| 1024| 32| 13578M| 1.3.27504|
ggml_backend_sycl_set_mul_device_mode: true
detect 1 SYCL GPUs: [0] with top Max compute units:128
llm_load_tensors: ggml ctx size = 0.28 MiB
llm_load_tensors: offloading 24 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 25/25 layers to GPU
llm_load_tensors: SYCL0 buffer size = 363.36 MiB
llm_load_tensors: CPU buffer size = 121.71 MiB
...................................................
llama_new_context_with_model: n_ctx = 512
llama_new_context_with_model: n_batch = 512
llama_new_context_with_model: n_ubatch = 512
llama_new_context_with_model: flash_attn = 0
llama_new_context_with_model: freq_base = 1000000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init: SYCL0 KV buffer size = 48.00 MiB
llama_new_context_with_model: KV self size = 48.00 MiB, K (f16): 24.00 MiB, V (f16): 24.00 MiB
llama_new_context_with_model: SYCL_Host output buffer size = 1.16 MiB
llama_new_context_with_model: SYCL0 compute buffer size = 298.75 MiB
llama_new_context_with_model: SYCL_Host compute buffer size = 3.01 MiB
llama_new_context_with_model: graph nodes = 750
llama_new_context_with_model: graph splits = 2
{"tid":"4428","timestamp":1719324259,"level":"INFO","function":"init","line":715,"msg":"initializing slots","n_slots":1}
{"tid":"4428","timestamp":1719324259,"level":"INFO","function":"init","line":727,"msg":"new slot","id_slot":0,"n_ctx_slot":512}
{"tid":"4428","timestamp":1719324259,"level":"INFO","function":"main","line":3040,"msg":"model loaded"}
{"tid":"4428","timestamp":1719324259,"level":"INFO","function":"main","line":3065,"msg":"chat template","chat_example":"<|im_start|>system\nYou are a helpful assistant<|im_end|>\n<|im_start|>user\nHello<|im_end|>\n<|im_start|>assistant\nHi there<|im_end|>\n<|im_start|>user\nHow are you?<|im_end|>\n<|im_start|>assistant\n","built_in":true}
{"tid":"4428","timestamp":1719324259,"level":"INFO","function":"main","line":3793,"msg":"HTTP server listening","hostname":"127.0.0.1","port":"8080","n_threads_http":"21"}
{"tid":"4428","timestamp":1719324259,"level":"INFO","function":"update_slots","line":1812,"msg":"all slots are idle"}
rnwang04
YixinSong-e
Log output: